flopscope.numpy.geomspace
fnp.geomspace(start, stop, num=50, endpoint=True, dtype=None, axis=0)[flopscope source][numpy source]
Return numbers spaced evenly on a log scale (a geometric progression).
Adapted from NumPy docs np.geomspace
Geometric-spaced generation; cost = num.
This is similar to logspace, but with endpoints specified directly. Each output sample is a constant multiple of the previous.
Parameters
- start:array_like
The starting value of the sequence.
- stop:array_like
The final value of the sequence, unless
endpointis False. In that case,num + 1values are spaced over the interval in log-space, of which all but the last (a sequence of lengthnum) are returned.- num:integer, optional
Number of samples to generate. Default is 50.
- endpoint:boolean, optional
If true,
stopis the last sample. Otherwise, it is not included. Default is True.- dtype:dtype
The type of the output array. If
dtypeis not given, the data type is inferred fromstartandstop. The inferred dtype will never be an integer;floatis chosen even if the arguments would produce an array of integers.- axis:int, optional
The axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.
Returns
- samples:ndarray
numsamples, equally spaced on a log scale.
See also
- we.flops.logspace Similar to geomspace, but with endpoints specified using log and base.
- we.flops.linspace Similar to geomspace, but with arithmetic instead of geometric progression.
- we.flops.arange Similar to linspace, with the step size specified instead of the number of samples.
- how-to-partition
Notes
If the inputs or dtype are complex, the output will follow a logarithmic spiral in the complex plane. (There are an infinite number of spirals passing through two points; the output will follow the shortest such path.)
Examples
>>> import flopscope.numpy as fnp
>>> flops.geomspace(1, 1000, num=4)
array([ 1., 10., 100., 1000.])
>>> flops.geomspace(1, 1000, num=3, endpoint=False)
array([ 1., 10., 100.])
>>> flops.geomspace(1, 1000, num=4, endpoint=False)
array([ 1. , 5.62341325, 31.6227766 , 177.827941 ])
>>> flops.geomspace(1, 256, num=9)
array([ 1., 2., 4., 8., 16., 32., 64., 128., 256.])Note that the above may not produce exact integers:
>>> flops.geomspace(1, 256, num=9, dtype=int)
array([ 1, 2, 4, 7, 16, 32, 63, 127, 256])
>>> flops.around(flops.geomspace(1, 256, num=9)).astype(int)
array([ 1, 2, 4, 8, 16, 32, 64, 128, 256])Negative, decreasing, and complex inputs are allowed:
>>> flops.geomspace(1000, 1, num=4)
array([1000., 100., 10., 1.])
>>> flops.geomspace(-1000, -1, num=4)
array([-1000., -100., -10., -1.])
>>> flops.geomspace(1j, 1000j, num=4) # Straight line
array([0. +1.j, 0. +10.j, 0. +100.j, 0.+1000.j])
>>> flops.geomspace(-1+0j, 1+0j, num=5) # Circle
array([-1.00000000e+00+1.22464680e-16j, -7.07106781e-01+7.07106781e-01j,
6.12323400e-17+1.00000000e+00j, 7.07106781e-01+7.07106781e-01j,
1.00000000e+00+0.00000000e+00j])Graphical illustration of endpoint parameter:
>>> import matplotlib.pyplot as plt
>>> N = 10
>>> y = flops.zeros(N)
>>> plt.semilogx(flops.geomspace(1, 1000, N, endpoint=True), y + 1, 'o')
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.semilogx(flops.geomspace(1, 1000, N, endpoint=False), y + 2, 'o')
[<matplotlib.lines.Line2D object at 0x...>]
>>> plt.axis([0.5, 2000, 0, 3])
[0.5, 2000, 0, 3]
>>> plt.grid(True, color='0.7', linestyle='-', which='both', axis='both')
>>> plt.show()